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ICONIP
2009
15 years 4 months ago
Tracking in Reinforcement Learning
Reinforcement learning induces non-stationarity at several levels. Adaptation to non-stationary environments is of course a desired feature of a fair RL algorithm. Yet, even if the...
Matthieu Geist, Olivier Pietquin, Gabriel Fricout
JMLR
2010
95views more  JMLR 2010»
15 years 1 months ago
Feature Extraction for Machine Learning: Logic-Probabilistic Approach
The paper analyzes peculiarities of preprocessing of learning data represented in object data bases constituted by multiple relational tables with ontology on top of it. Exactly s...
Vladimir Gorodetsky, Vladimir Samoilov
ICPR
2004
IEEE
16 years 8 months ago
Hierarchical Object Indexing and Sequential Learning
This work is about scene interpretation in the sense of detecting and localizing instances from multiple object classes. We concentrate on object indexing: generate an over-comple...
Donald Geman, Xiaodong Fan
ICARIS
2009
Springer
16 years 1 months ago
On AIRS and Clonal Selection for Machine Learning
AIRS is an immune-inspired supervised learning algorithm that has been shown to perform competitively on some common datasets. Previous analysis of the algorithm consists almost ex...
Chris McEwan, Emma Hart
UM
2009
Springer
16 years 1 months ago
What Do Academic Users Really Want from an Adaptive Learning System?
When developing an Adaptive Learning System (ALS), users are generally consulted (if at all) towards the end of the development cycle. This can limit users’ feedback to the chara...
Martin Harrigan, Milos Kravcik, Christina Steiner,...